Abstract

This work studies optimal flow control of a micro grid consisting of households equipped
with μ-CHP devices and gas and heat buffers. Agricultural wastes from households are
used to produce biogas by a biogas generator. The produced biogas is, then, utilized
to fulfill local demand of heat and power of the households. Excess biogas can be
upgraded and sold to the low pressure gas grid. Excess electricity produced by the μ-
CHPs of households can be also sold to the electricity grid. The aim of the control process
is to maximize the estimated profit of the households while avoiding overloading
gas and electricity grids and avoiding the biogas shortage. The decisions on the supply
and consumption levels are done in both centralized and distributed fashions using
model predictive control (MPC). The distributed MPC (dMPC) is developed from the
centralized MPC (cMPC) by employing dual decomposition method combined with
the projected sub-gradient method. In dMPC, each household makes decisions based
on its local information, yet still needs to coordinate its supply and consumption bids to
the grid operators and the biogas generator. The coordinations are formulated for synchronous
and asynchronous implementations. With the distributed scheme, the grid
operators and the biogas producer can manage households’ supply and consumption
levels via dynamic pricing to obey the grid capacity constraints. We perform extensive
simulations to investigate the behavior of dynamic pricing modified by the grid
operators and the biogas generator. Furthermore, we provide numerical results to compare
the performance of cMPC, synchronous dMPC, and asynchronous dMPC using
realistic estimates of the selling prices and demand patterns.